Retain your customers with customer churn prediction

Retail_customer-churn

The retail industry survives on the customers it has. The profit of a retail store is usually defined by the overall sale it does in a given duration of time. Sometimes, in that particular time frame, a retailer may gain or lose a customer to its competitors. Gaining is always a plus for the business, however, losing a customer leads to customer churn.

Customer churn occurs when a customer stops using a retailer’s product, stops visiting a particular retail store, switch to lower-tier experience or switch to competitor’s products. Retailers need a sure-shot strategy to manage customer churn. Measuring the churn rate is quite crucial for retail businesses as the metric reflects customer response towards the product, service, price and competition. Customer churn minimizes the profit quotient of the business and may result in negative marketing of the brand/store.

The power of data and machine learning to retain the customers

In today’s fiercely competitive market, everything depends on the data that is generated during a process. But, how can this data actually help a retailer to retain the customers? This is where, SIA –Softweb Intelligence and Analytics platform comes in handy.

SIA can offer the much needed insight to lower down the churn ratio for a retail store. The platform can capture, analyze and visually represent the data whilst providing concrete predictions based on the pattern of purchase, number of revisits and amount of purchase done by a customer.

With Softweb Intelligence and Analytics platform’s insights a retailer can focus on their marketing efforts and sales strategies that can help in gaining a competitive edge with a lowered customer churn ratio.

Impact of SIA to lower churn ratio

  • Personalized marketing offers
  • Analyze the number of revisits
  • Compare the historical patterns of sales of the customer
  • Advanced algorithms and decision trees to derive insights from various customers
Talk to us about your data complexities and let SIA address them